Noometry

Model comparison

Mixtral 8x22B vs Qwen3.6 27B

Qwen3.6 27B is the stronger model overall, scoring 41.9 to 26.7 on the Noometry Index.

Last verified . 3 shared benchmarks.

Mixtral 8x22B Mistral AI

26.7

Rank #330 Confirmed

Qwen3.6 27B Alibaba (Qwen)

41.9

Rank #112 Confirmed

Summary

  • They share 3 benchmarks with published results for both. Mixtral 8x22B scores higher in 0 categories and Qwen3.6 27B in 5 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 15.1.
  • The biggest single-benchmark swing is GPQA Diamond: 34.1% for Mixtral 8x22B and 85.9% for Qwen3.6 27B.
  • Qwen3.6 27B is cheaper at $0.60 / $3.60 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
  • Qwen3.6 27B accepts more context: 262K tokens versus 64K.

Side by side

Mixtral 8x22BQwen3.6 27B
ProviderMistral AIAlibaba (Qwen)
Noometry Index26.741.9
Released2024-04-172026-04-22
WeightsOpenOpen
Context window64K262K
Max output64K66K
Input $ / M tokens$2$0.60
Output $ / M tokens$6$3.60
Results tracked3411

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Category by category

Coding Qwen3.6 27B leads

Mixtral 8x22B: 23.8 (#324), Qwen3.6 27B: 38.5 (#162)

BenchmarkMixtral 8x22BQwen3.6 27B
SciCode—37.3%
WeirdML3.2%—
BigCodeBench Instruct40.6%—
LMArena Coding1166—
BigCodeBench Complete50.2%—
HumanEval+72%—
MBPP+64.3%—

Agentic & Tool Use Not comparable

Mixtral 8x22B: 22.8 (#119), Qwen3.6 27B: —

BenchmarkMixtral 8x22BQwen3.6 27B
Cybench7.5%—

Reasoning Qwen3.6 27B leads

Mixtral 8x22B: 19.1 (#246), Qwen3.6 27B: 24.4 (#148)

BenchmarkMixtral 8x22BQwen3.6 27B
DTBench55.1%78.1%
Epoch Capabilities Index122146.47
CritPt—0.9%
Chess Puzzles—22%
LMArena Hard Prompts1150—
Mystery Game Puzzles—7%
LMCA—34.5%
ForecastBench56.3—

Math Qwen3.6 27B leads

Mixtral 8x22B: 21.2 (#271), Qwen3.6 27B: 47.5 (#56)

BenchmarkMixtral 8x22BQwen3.6 27B
FrontierMath (Tiers 1-3)—35.1%
OTIS Mock AIME 2024-2025—91.1%
Omni-MATH16.3%—
LMArena Math1184—
MATH Level 524.2%—

Knowledge Qwen3.6 27B leads

Mixtral 8x22B: 15.1 (#288), Qwen3.6 27B: 52.4 (#58)

BenchmarkMixtral 8x22BQwen3.6 27B
GPQA Diamond34.1%85.9%
MMLU-Pro46%—
GPQA (HELM)33.4%—
LMArena Expert1113—
MMLU77.8%—

Multilingual Not comparable

Mixtral 8x22B: 32.9 (#250), Qwen3.6 27B: —

BenchmarkMixtral 8x22BQwen3.6 27B
LMArena Non-English1128—
LMArena Chinese1116—
LMArena French1165—
LMArena German1141—
LMArena Japanese1037—
LMArena Korean1056—
LMArena Russian1158—
LMArena Spanish1150—

Instruction Following Not comparable

Mixtral 8x22B: 57.9 (#261), Qwen3.6 27B: —

BenchmarkMixtral 8x22BQwen3.6 27B
IFEval72.4%—
LMArena Instruction Following1147—

Long Context Not comparable

Mixtral 8x22B: 34.6 (#242), Qwen3.6 27B: —

BenchmarkMixtral 8x22BQwen3.6 27B
LMArena Longer Query1144—

Writing & Preference Qwen3.6 27B leads

Mixtral 8x22B: 37.1 (#257), Qwen3.6 27B: 50.3 (#180)

BenchmarkMixtral 8x22BQwen3.6 27B
LMArena Text1162—
LMArena Creative Writing1141—
WildBench71.1%—
EQ-Bench 4—1026
LMArena Multi-Turn1130—

Frequently asked questions

Is Mixtral 8x22B better than Qwen3.6 27B?

Qwen3.6 27B is the stronger model overall, scoring 41.9 to 26.7 on the Noometry Index.

Which is cheaper, Mixtral 8x22B or Qwen3.6 27B?

Qwen3.6 27B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; Mixtral 8x22B lists at $2 and $6.

Is Mixtral 8x22B or Qwen3.6 27B better for coding?

Qwen3.6 27B scores higher on coding benchmarks: 38.5 versus 23.8 in the Noometry coding category.

Which has the bigger context window?

Qwen3.6 27B does, with 262K tokens against 64K.

How many benchmarks do Mixtral 8x22B and Qwen3.6 27B share?

3 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and Qwen3.6 27B has 11.

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